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On Optimal Satisficing: How Simple Policies Can Achieve Excellent Results

In: Decision Modeling and Behavior in Complex and Uncertain Environments

Author

Listed:
  • J. Neil Bearden

    (University of Arizona)

  • Terry Connolly

    (University of Arizona)

Abstract

Herbert Simon introduced the notion of satisficing to explain how boundedly rational agents might approach difficult sequential decision problems. His satisficing decision makers were offered as an alternative to optimizers, who need impressive computational capacities in order to maximize their payoffs. In this chapter, we present a simplified sequential search problem for a satisficing decision maker, and show how to compute its optimal satisficing search policies. Our analyses provide bounds on the performance of satisficing search policies.

Suggested Citation

  • J. Neil Bearden & Terry Connolly, 2008. "On Optimal Satisficing: How Simple Policies Can Achieve Excellent Results," Springer Optimization and Its Applications, in: Tamar Kugler & J. Cole Smith & Terry Connolly & Young-Jun Son (ed.), Decision Modeling and Behavior in Complex and Uncertain Environments, pages 79-97, Springer.
    • Handle: RePEc:spr:spochp:978-0-387-77131-1_4
    DOI: 10.1007/978-0-387-77131-1_4
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    Citations

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    Cited by:

    1. Tine Bertoncel & Ivan Erenda & Maja Meško, 2018. "Best Practices. Managerial Early Warning System as Best Practice for Project Selection at a Smart Factory," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 20(49), pages 805-805, August.
    2. Dinko Dimitrov & Saptarshi Mukherjee & Nozomu Muto, 2016. "‘Divide-and-choose’ in list-based decision problems," Theory and Decision, Springer, vol. 81(1), pages 17-31, June.
    3. repec:aud:audfin:v:20:y:2018:i:49:p:805 is not listed on IDEAS
    4. Carina Burs & Thomas Gries, 2022. "Decision-making under Imperfect Information with Bayesian Learning or Heuristic Rules," Working Papers CIE 149, Paderborn University, CIE Center for International Economics.
    5. Engwerda, J.C., 2012. "Prospects of Tools from Differential Games in the Study Of Macroeconomics of Climate Change," Discussion Paper 2012-045, Tilburg University, Center for Economic Research.
    6. Berg, Nathan & Prakhya, Srinivas & Ranganathan, Kavitha, 2018. "A satisficing approach to eliciting risk preferences," Journal of Business Research, Elsevier, vol. 82(C), pages 127-140.
    7. Chun, Young H., 2015. "Multi-attribute sequential decision problem with optimizing and satisficing attributes," European Journal of Operational Research, Elsevier, vol. 243(1), pages 224-232.

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